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pybind_state_dlpack.h
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#pragma once
#include "caffe2/core/context.h"
#include "caffe2/core/tensor.h"
#include "caffe2/core/types.h"
#include "caffe2/proto/caffe2_pb.h"
#include "caffe2/python/dlpack.h"
#include <pybind11/pybind11.h>
#include <pybind11/stl.h>
namespace caffe2 {
namespace python {
namespace py = pybind11;
const DLDeviceType* CaffeToDLDeviceType(int device_type);
const DLDataType* CaffeToDLType(const TypeMeta meta);
const TypeMeta DLTypeToCaffe(const DLDataType& dl_type);
// TODO: remove context
template <class Context>
class DLPackWrapper {
public:
DLPackWrapper(Tensor* tensor, DeviceOption device_option)
: tensor(tensor), device_option(device_option) {}
py::object data() {
DLDevice tensor_context;
auto device_type_ptr = CaffeToDLDeviceType(device_option.device_type());
CAFFE_ENFORCE(
device_type_ptr,
"Unsupported device type: ",
device_option.device_type());
tensor_context.device_type = *device_type_ptr;
tensor_context.device_id = device_option.device_id();
if (tensor->numel() <= 0) {
tensor->Resize(0);
}
if (tensor->dtype() == ScalarType::Undefined) {
// treat uninitialized tensor as float tensor
tensor->template mutable_data<float>();
}
CAFFE_ENFORCE_GT(tensor->dim(), 0);
auto type_ptr = CaffeToDLType(tensor->dtype());
CAFFE_ENFORCE(
type_ptr,
"Tensor type is not supported in DLPack: ",
tensor->dtype().name());
DLDataType tensor_type = *type_ptr;
DLTensor dlTensor;
dlTensor.data = const_cast<void*>(tensor->raw_data());
dlTensor.device = tensor_context;
dlTensor.ndim = tensor->dim();
dlTensor.dtype = tensor_type;
dlTensor.shape = const_cast<int64_t*>(&(tensor->sizes()[0]));
dlTensor.strides = nullptr;
dlTensor.byte_offset = 0;
managed_tensor.dl_tensor = dlTensor;
// C2 Tensor memory is managed by C2
managed_tensor.manager_ctx = nullptr;
managed_tensor.deleter = [](DLManagedTensor*) {};
return py::reinterpret_steal<py::object>(
PyCapsule_New(&managed_tensor, "dltensor", nullptr));
}
void feed(py::object obj) {
CAFFE_ENFORCE(PyCapsule_CheckExact(obj.ptr()), "Expected DLPack capsule");
DLManagedTensor* dlMTensor =
(DLManagedTensor*)PyCapsule_GetPointer(obj.ptr(), "dltensor");
CAFFE_ENFORCE(dlMTensor, "Invalid DLPack capsule");
DLTensor* dlTensor = &dlMTensor->dl_tensor;
auto device_type_ptr = CaffeToDLDeviceType(device_option.device_type());
CAFFE_ENFORCE(
device_type_ptr,
"Unsupported device type: ",
device_option.device_type());
CAFFE_ENFORCE(
dlTensor->device.device_type == *device_type_ptr,
"DLPack tensor device type mismatch");
int dlpack_device_id = dlTensor->device.device_id;
CAFFE_ENFORCE_EQ(
dlpack_device_id,
device_option.device_id(),
"Expected same device id for DLPack and C2 tensors");
std::vector<int64_t> dims;
dims.reserve(dlTensor->ndim);
for (int idx = 0; idx < dlTensor->ndim; ++idx) {
dims.push_back(dlTensor->shape[idx]);
}
if (dlTensor->strides) {
int64_t stride = 1;
for (int idx = dims.size() - 1; idx >= 0; --idx) {
CAFFE_ENFORCE_EQ(
stride,
dlTensor->strides[idx],
"Tensors with non-standard strides are not supported");
stride *= dims[idx];
}
}
tensor->Resize(dims);
caffe2::TypeMeta meta = DLTypeToCaffe(dlTensor->dtype);
at::Device device = at::Device(tensor->GetDeviceType());
tensor->ShareExternalPointer(
at::DataPtr(
(void*)(((int8_t*)dlTensor->data) + dlTensor->byte_offset),
static_cast<void*>(dlMTensor),
[](void* t_ptr) -> void {
DLManagedTensor* mt_ptr = static_cast<DLManagedTensor*>(t_ptr);
if (mt_ptr->deleter) {
mt_ptr->deleter(mt_ptr);
}
},
device),
meta,
0);
}
Tensor* tensor;
DeviceOption device_option;
DLManagedTensor managed_tensor;
};
} // namespace python
} // namespace caffe2